Improved Method of Text Similarity Measurement

1. A method for estimating the similarity between at least two portions of text, said method comprising the steps of: receiving said at least two portions of text; forming a set of syntactic tuples from said portions of text, each tuple comprising two terms and a relation between the two terms; classifying the relation between the terms in the tuples according to a predefined set of relations; predefining classes of agreement between tuples under comparison, comprising a class of full agreement wherein tuples under comparison are identical, a class of partial agreement wherein only two of corresponding elements in tuples under comparison are identical, and a class of term agreement wherein only one of corresponding terms in tuples under comparison are identical; determining a respective class of relative agreement between each pair of syntactic tuples from the portions of text under comparison according to the predefined classes of agreement; calculating a value representative of the similarity between the portions of text for each of the classes of agreement, based on the plurality of tuples determined to belong to the respective class of agreement; and determining and outputting a measure of the similarity between the portions of text by calculating a weighted sum of the values representative of the similarity between the portions of text for each of the classes of agreement.

2. A method according to claim 1 wherein the step of calculating a value representative of the similarity between the portions of text for each of the classes of agreement comprises a weighting based upon the number of matched terms occurring in particular parts of speech.

3. A method according to claim 2 wherein the step of calculating a value representative of the similarity between the portions of text for each of the classes of agreement comprises the application of a weighting factor to the estimate of similarity for each of the classes of agreement and the parts of speech in which matched terms occur.

4. A method according to claim 1 wherein the syntactic tuples comprise two terms and a relation between the terms, the relation being classified according to one of the following classes: relations between a verb and its subject; relations between a verb and its object; relations between a modifier and its modified word; or a circumstantial relationship.

5. A method according to claim 1 wherein the syntactic tuples are of the form (relation, term1, term2).

11. A method according to claim 10 wherein a syntactic tuple of a first portion of text, T i , and a syntactic tuple of a second portion of text, T j , are associated with a class of a part of speech, POS3, if they are not associated with either class POS1 or POS2.

12. A method according to claim 11 wherein the step of calculating a value representative of the similarity between the portions of text for each of the classes of agreement comprises a weighting based upon the number of matched terms occurring in particular parts of speech, the calculation of the value for Class A comprising parameters relating to the number of matching syntactic tuples according to Class A and POS1, nA 1 , the number of matching syntactic tuples according to Class A and POS2, nA 2 , and the number of matching syntactic tuples according to Class A and POS3, nA 3 , and separate weighting factors w 1 , w 2 and w 3 also being applied to the POS1, POS2 and POS3 matchings, the value, sim A (D i ,D J ), being calculated as: sim A ⁡ ( D i , D j ) = ∑ i = 1 3 ⁢ ⁢ n ⁢ ⁢ A i · w i min ⁡ ( N i , N j ) where min(N i ,N j ) represents the lesser value of the two lengths of the vectors of syntactic tuples formed for the portions of text D i and D j , respectively.

13. A method according to claim 12 wherein the step of calculating a value representative of the similarity between the portions of text for each of the classes of agreement comprises a weighting based upon the number of matched terms occurring in particular parts of speech, the calculation of the value for Class B comprising parameters relating to the number of matching syntactic tuples according to Class B and POS1, nB 1 , the number of matching syntactic tuples according to Class B and POS2, nB 2 , and the number of matching syntactic tuples according to Class B and POS3, nB 3 , and separate weighting factors w 1 , w 2 and w 3 also being applied to the POS1, POS2 and POS3 matchings, the value, sim B (D i ,D j ), being calculated as: sim B ⁡ ( D i , D j ) = ∑ i = 1 3 ⁢ ⁢ n ⁢ ⁢ B i · w i 3 · min ⁡ ( N i , N j ) where min(N i ,N j ) represents the lesser value of the two lengths of the vectors of syntactic tuples formed for the portions of text D i and D j respectively.

14. A method according to claim 13 wherein the step of calculating a value representative of the similarity between the portions of text for each of the classes of agreement comprises a weighting based upon the number of matched terms occurring in particular parts of speech, the calculation of the value for Class C comprising parameters relating to the number of matching syntactic tuples according to Class C and POS1, nC 1 , the number of matching syntactic tuples according to class C and POS2, nC 2 , and the number of matching syntactic tuples according to Class C and POS3, nC 3 , and separate weighting factors w 1 , w 2 and w 3 also being applied to the POS1, POS2 and POS3 matchings, the value, sim c (D i ,D j ), being calculated as: sim C ⁡ ( D i , D j ) = ∑ i = 1 3 ⁢ ⁢ n ⁢ ⁢ C i · w i 2 · min ⁡ ( N i , N j ) where min(N i , N j ) represents the lesser value of the two lengths of the vectors of syntactic tuples formed for the portions of text D i and D j respectively.